March 2023 arXiv papers — page 49

Zhituo Wang

We study the low temperature properties of the two-dimensional weakly interacting Hubbard model on $\ZZZ^2$ with renormalized chemical potential $\mu=2-\mu_0$, $\mu_0=10^{-10}$ fixed, in which case the Fermi surface is close to a perfect square. Using fermionic functional integrals, cluster expansions and rigorous renormalization group analysis, we prove tha

Erol Gelenbe, Mert Nakıp

Botnet attacks are a major threat to networked systems because of their ability to turn the network nodes that they compromise into additional attackers, leading to the spread of high volume attacks over long periods. The detection of such Botnets is complicated by the fact that multiple network IP addresses will be simultaneously compromised, so that Collec

Wenrui Miao, Yongtao Zhang, Greg Gbur

It has long been assumed that there is an intrinsic conflict between optical vortices and partial coherence, in that deterministic phase vortices do not appear in partially coherent fields. We demonstrate, however, that it is possible to construct a beam that has no deterministic vortices in the source plane yet evolves a deterministic vortex at a specified

Claudiu Mîndrilă, Sebastian Schwarzacher

In many occurrences of fluid-structure interaction time-periodic motions are observed. We consider the interaction between a fluid driven by the three dimensional Navier-Stokes equation and a two dimensional linearized elastic Koiter shell situated at the boundary. The fluid-domain is a part of the solution and as such changing in time periodically. On a ste

Nora Hille, Berenike Bürvenich, Felix Carros, Mehrbod Manavi

Often robots are seen as a means to an end to fulfill a logical objective task. Android robots, on the other hand, provide new possibilities to fulfill emotional tasks and could therefore be integrated into assistive scenarios. We explored this possibility by letting older adults and stakeholders have a conversation with an android robot capable of expressin

S. R. Elliott, V. N. Gavrin, W. C. Haxton, T. V. Ibragimova

In the recent Baksan Experiment on Sterile Transitions (BEST), a suppressed rate of neutrino absorption on a gallium target was observed, consistent with earlier results from neutrino source calibrations of the SAGE and GALLEX/GNO solar neutrino experiments. The BEST collaboration, utilizing a 3.4 MCi 51Cr neutrino source, found observed-to-expected counting

The H1 collaboration, V. Andreev, M. Arratia, A. Baghdasaryan

The radiation pattern within high energy quark- and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as an environment for optimizing event generators with numerous applications in high energy particle and nuclear physics. Looking at electron-proton collisions is of particular interest as many of th

Brian Buckley, Adrian O'Hagan, Marie Galligan

Bayesian approaches to clinical analyses for the purposes of patient phenotyping have been limited by the computational challenges associated with applying the Markov-Chain Monte-Carlo (MCMC) approach to large real-world data. Approximate Bayesian inference via optimization of the variational evidence lower bound, often called Variational Bayes (VB), has bee

Ilan Mandel, Wendy Ju

In our practice as educators, researchers and designers we have found that centering reverse engineering and reuse has pedagogical, environmental, and economic benefits. Design decisions in the development of new hardware tool-kits should consider how we can use e-waste at hand as integral components of electronics prototyping. Dissection, extraction and mod

Robert B. Griffiths

Developing a quantum analog of the modern classical theory of causation, as formulated by Pearl and others using directed acyclic graphs, requires a theory of random or stochastic time development at the microscopic level, where the noncommutation of Hilbert-space projectors cannot be ignored. The Consistent Histories approach provides such a theory. How it

Shiwei Feng, Guanhong Tao, Siyuan Cheng, Guangyu Shen

Self-supervised learning in computer vision trains on unlabeled data, such as images or (image, text) pairs, to obtain an image encoder that learns high-quality embeddings for input data. Emerging backdoor attacks towards encoders expose crucial vulnerabilities of self-supervised learning, since downstream classifiers (even further trained on clean data) may

Louis G. Christie, John A. D. Aston

We present a method for estimating the maximal symmetry of a continuous regression function. Knowledge of such a symmetry can be used to significantly improve modelling by removing the modes of variation resulting from the symmetries. Symmetry estimation is carried out using hypothesis testing for invariance strategically over the subgroup lattice of a searc

Douglas P. Holmes

How do we characterize the shape of a surface? It is now well understood that the shape of a surface is determined by measuring how curved it is at each point. From these measurements, one can identify the directions of largest and smallest curvature, i.e. the principal curvatures, and construct two surface invariants by taking the average and the product of

Michele Pernice

This paper is the fourth in a series of four papers aiming to describe the (almost integral) Chow ring of $\overline{\mathcal{M}}_3$, the moduli stack of stable curves of genus $3$. In this paper, we finally compute the Chow ring of $\overline{\mathcal{M}}_3$ with $\mathbb{Z}[1/6]$-coefficients.

ATLAS Collaboration

A search for heavy long-lived multi-charged particles is performed using the ATLAS detector at the LHC. Data collected in 2015-2018 at $\sqrt{s}$ = 13 TeV from $pp$ collisions corresponding to an integrated luminosity of 139 fb$^{-1}$ are examined. Particles producing anomalously high ionization, consistent with long-lived spin-1/2 massive particles with ele

Van Nguyen Nguyen, Thibault Groueix, Yinlin Hu, Mathieu Salzmann

The practicality of 3D object pose estimation remains limited for many applications due to the need for prior knowledge of a 3D model and a training period for new objects. To address this limitation, we propose an approach that takes a single image of a new object as input and predicts the relative pose of this object in new images without prior knowledge o

Min Gao, Tristan T. Hormel, Yukun Guo, Kotaro Tsuboi

Purpose: Microaneurysms (MAs) have distinct, oval-shaped, hyperreflective walls on structural OCT, and inconsistent flow signal in the lumen with OCT angiography (OCTA). Their relationship to regional macular edema in diabetic retinopathy (DR) has not been quantitatively explored. Participants: A total of 99 participants, including 23 with mild, NPDR, 25 wit

Todd C. Hollon, Cheng Jiang, Asadur Chowdury, Mustafa Nasir-Moin

Molecular classification has transformed the management of brain tumors by enabling more accurate prognostication and personalized treatment. However, timely molecular diagnostic testing for patients with brain tumors is limited, complicating surgical and adjuvant treatment and obstructing clinical trial enrollment. In this study, we developed DeepGlioma, a

Roman Jacome, Edwin Vargas, Kumar Vijay Mishra, Brian M. Sadler

In joint radar-communications (JRC) applications such as secure military receivers, often the radar and communications signals are overlaid in the received signal. In these passive listening outposts, the signals and channels of both radar and communications are unknown to the receiver. The ill-posed problem of recovering all signal and channel parameters fr

Büsra Kösoglu-Kind, Robert Loredo, Michele Grossi, Christian Bernecker

Genetic information is encoded in a linear sequence of nucleotides, represented by letters ranging from thousands to billions. Mutations refer to changes in the DNA or RNA nucleotide sequence. Thus, mutation detection is vital in all areas of biology and medicine. Careful monitoring of virulence-enhancing mutations is essential. However, an enormous amount o

Keping Xie, Jun Gao, T. J. Hobbs, Daniel R. Stump

We present a state-of-the-art prediction for cross sections of neutrino deep inelastic scattering (DIS) from nucleon at high neutrino energies, $E_\nu$, from 100 GeV to 1000 EeV ($10^{12}$ GeV). Our calculations are based on the latest CT18 NNLO parton distribution functions (PDFs) and their associated uncertainties. In order to make predictions for the high

Tim Lebailly, Thomas Stegmüller, Behzad Bozorgtabar, Jean-Philippe Thiran

Most self-supervised methods for representation learning leverage a cross-view consistency objective i.e., they maximize the representation similarity of a given image's augmented views. Recent work NNCLR goes beyond the cross-view paradigm and uses positive pairs from different images obtained via nearest neighbor bootstrapping in a contrastive setting. We

Yizhe Tang

Mg represents a group of technically important hexagonal-close packed (hcp) metals whose mechanical behaviors are very different from body-centered cubic (bcc) and face-centered cubic (fcc) metals and the underlying mechanisms remain poorly-understood. It has been long known that Mg has high hardening and low ductility, and this was conventionally attributed

Mohammad Pedramfar, Vaneet Aggarwal

This paper investigates the problem of combinatorial multiarmed bandits with stochastic submodular (in expectation) rewards and full-bandit delayed feedback, where the delayed feedback is assumed to be composite and anonymous. In other words, the delayed feedback is composed of components of rewards from past actions, with unknown division among the sub-comp

Rusiru Gambheera, Cristian D. Popescu

We improve upon the recent keystone result of Dasgupta-Kakde on the $\Bbb Z[G(H/F)]^-$-Fitting ideals of certain Selmer modules $Sel_S^T(H)^-$ associated to an abelian, CM extension $H/F$ of a totally real number field $F$ and use this to compute the $\Bbb Z_p[[G(H_\infty/F)]]^-$-Fitting ideal of the Iwasawa module analogues $Sel_S^T(H_\infty)_p^-$ of these

Yves H. Kwan, Glenn Wagner, Nick Bultinck, Steven H. Simon

Recent scanning tunneling microscopy experiments [K.P. Nuckolls et al., arXiv:2303.00024] have revealed the ubiquity of Kekul\'e charge-density wave order in magic-angle twisted bilayer graphene. Most samples are moderately strained and show `incommensurate Kekul\'e spiral' (IKS) order involving a graphene-scale charge density distortion uniaxially modulated

Yangyang Chang, Gerald E. Sobelman

Quantization using a small number of bits shows promise for reducing latency and memory usage in deep neural networks. However, most quantization methods cannot readily handle complicated functions such as exponential and square root, and prior approaches involve complex training processes that must interact with floating-point values. This paper proposes a

Victor Enguita-Vileta, Belen Gavela, Rachel Houtz, Pablo Quilez

Exact discrete symmetries, if non-linearly realized, can reduce the ultraviolet sensitivity of a given theory. The scalars stemming from spontaneous symmetry breaking are massive without breaking the discrete symmetry, and those masses are protected from divergent quadratic corrections. This is in contrast to non-linearly realized continuous symmetries. The

M. Di Martino, P. Linke, E. N. Pistikopoulos

The energy-water demands of metropolitan regions and agricultural ecosystems are ever-increasing. To tackle this challenge efficiently and sustainably, the interdependence of these interconnected resources has to be considered. In this work, we present a holistic decision-making framework which takes into account simultaneously a water and energy supply syst

Matias D. Cattaneo, Michael Jansson, Kenichi Nagasawa

Westling and Carone (2020) proposed a framework for studying the large sample distributional properties of generalized Grenander-type estimators, a versatile class of nonparametric estimators of monotone functions. The limiting distribution of those estimators is representable as the left derivative of the greatest convex minorant of a Gaussian process whose

Adi Armoni, Ricardo Stuardo

We study the dynamics of an 'electric' $\mathcal{N}=1$ 3D $U(N_c)_{k,k+\frac{N_c}{2}}$ SQCD theory. By embedding the theory in string theory, we propose that the theory admits a 'magnetic' dual and analyse the low energy dynamics of the theory using its dual. When $\frac{N_f}{2} \ge\frac{N_c}{2}-k$ the IR dynamics is described by either a TQFT for large quar

Leron Borsten, Branislav Jurco, Hyungrok Kim, Tommaso Macrelli

We prove that the tree-level scattering amplitudes for (super) Yang-Mills theory in arbitrary dimensions and for M2-brane models exhibit color-kinematics (CK) duality. Our proof for Yang-Mills theory substantially simplifies existing ones in that it relies on the action alone and does not involve any computation; the proof for M2-brane models establishes thi

Jeremy Hare, George G. Pavlov, Oleg Kargaltsev, Gordon P. Garmire

LS 2883/PSR B1259-63 is a high mass, eccentric gamma-ray binary that has previously been observed to eject X-ray emitting material. We report the results of recent Chandra observations near binary apastron in which a new X-ray emitting clump of matter was detected. The clump has a high projected velocity of $v_{\perp}\approx 0.07c$ and hard X-ray spectrum, w

Sankhayan Mukherjee, Swapan Kumar Patra

This study is a survey of digital library initiatives in India collecting secondary information from about fifty digital libraries from their respective websites. The findings show that in most cases the actual conception of the digital library is still in a nascent stage. Online subscriptions and links to third-party websites are also considered digital lib

Felix Rydell, Elima Shehu, Angelica Torres

We study the joint image of lines incident to points, meaning the set of image tuples obtained from fixed cameras observing a varying 3D point-line incidence. We prove a formula for the number of complex critical points of the triangulation problem that aims to compute a 3D point-line incidence from noisy images. Our formula works for an arbitrary number of

Zheng-Xin Yong, Ruochen Zhang, Jessica Zosa Forde, Skyler Wang

While code-mixing is a common linguistic practice in many parts of the world, collecting high-quality and low-cost code-mixed data remains a challenge for natural language processing (NLP) research. The recent proliferation of Large Language Models (LLMs) compels one to ask: how capable are these systems in generating code-mixed data? In this paper, we explo

Patricio Arrué, Kaveh Laksari, Nima Toosizadeh

Frailty is a geriatric syndrome associated with the lack of physiological reserve and consequent adverse outcomes (therapy complications and death) in older adults. Recent research has shown associations between heart rate (HR) dynamics (HR changes during physical activity) with frailty. The goal of the present study was to determine the effect of frailty on

Paul Dufossé, Sébastien Benzekry

Survival analysis is an essential tool for the study of health data. An inherent component of such data is the presence of missing values. In recent years, researchers proposed new learning algorithms for survival tasks based on neural networks. Here, we studied the predictive performance of such algorithms coupled with different methods for handling missing

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

Generalization error predictors (GEPs) aim to predict model performance on unseen distributions by deriving dataset-level error estimates from sample-level scores. However, GEPs often utilize disparate mechanisms (e.g., regressors, thresholding functions, calibration datasets, etc), to derive such error estimates, which can obfuscate the benefits of a partic

Zi Wang, Somesh Jha, Krishnamurthy, Dvijotham

The neural network has become an integral part of modern software systems. However, they still suffer from various problems, in particular, vulnerability to adversarial attacks. In this work, we present a novel program reasoning framework for neural-network verification, which we refer to as symbolic reasoning. The key components of our framework are the use

Sepand Mavandadi, Tara N. Sainath, Ke Hu, Zelin Wu

We propose a new two-pass E2E speech recognition model that improves ASR performance by training on a combination of paired data and unpaired text data. Previously, the joint acoustic and text decoder (JATD) has shown promising results through the use of text data during model training and the recently introduced deliberation architecture has reduced recogni

Ruge Lin

In this article, we present a novel approach to investigating entanglement in the context of quantum computing. Our methodology involves analyzing reduced density matrices at different stages of a quantum algorithm's execution and representing the dominant eigenvalue and von Neumann entropy on a graph, creating an "entanglement trajectory." To establish the

Alejandro S. Borlaff, Enrique Lopez-Rodriguez, Rainer Beck, Susan E. Clark

We present the analysis of the magnetic field ($B$-field) structure of galaxies measured with far-infrared (FIR) and radio (3 and 6 cm) polarimetric observations. We use the first data release of the Survey on extragALactic magnetiSm with SOFIA (SALSA) of 14 nearby ($<20$ Mpc) galaxies with resolved (5 arcsec-18 arcsec; $90$ pc--$1$ kpc) imaging polarimetric

Alek Bedroya, Sanjay Raman, Houri-Christina Tarazi

We provide further motivation for the string lamppost principle in 9d supergravities. Using a blend of ideas which includes Swampland conjectures, finiteness of black hole entropy, and classification of SCFTs, we show that infinite distance limits that keep BPS states heavy must decompactify to type IIA supergravity on an interval. Without relying on string

Mark Booth, Tim D. Pearce, Alexander V. Krivov, Mark C. Wyatt

$\epsilon$ Eridani is the closest star to our Sun known to host a debris disc. Prior observations in the (sub-)millimetre regime have potentially detected clumpy structure in the disc and attributed this to interactions with an (as yet) undetected planet. However, the prior observations were unable to distinguish between structure in the disc and background

Joe S. Bright, Lauren Rhodes, Wael Farah, Rob Fender

The deaths of massive stars are sometimes accompanied by the launch of highly relativistic and collimated jets. If the jet is pointed towards Earth, we observe a "prompt" gamma-ray burst due to internal shocks or magnetic reconnection events within the jet, followed by a long-lived broadband synchrotron afterglow as the jet interacts with the circum-burst ma

Mikaela Angelina Uy, Ricardo Martin-Brualla, Leonidas Guibas, Ke Li

Neural radiance fields (NeRFs) have enabled high fidelity 3D reconstruction from multiple 2D input views. However, a well-known drawback of NeRFs is the less-than-ideal performance under a small number of views, due to insufficient constraints enforced by volumetric rendering. To address this issue, we introduce SCADE, a novel technique that improves NeRF re

Dhvanil D. Desai, Chris Ashall, Benjamin J. Shappee, Nidia Morrell

We present photometric and spectroscopic observations and analysis of SN 2021bxu (ATLAS21dov), a low-luminosity, fast-evolving Type IIb supernova (SN). SN 2021bxu is unique, showing a large initial decline in brightness followed by a short plateau phase. With $M_r = -15.93 \pm 0.16\, \mathrm{mag}$ during the plateau, it is at the lower end of the luminosity

Damian van de Heisteeg, Cumrun Vafa, Max Wiesner

The species scale $\Lambda_s\leq M_{pl}$ serves as a UV cutoff in the gravitational sector of an EFT and can depend on the moduli of the theory as the spectrum of the theory varies. We argue that the dependence of the species scale $\Lambda_s (\phi)$ on massless (or light) modes $\phi^i$ satisfies $M_{pl}^{d-2} |\Lambda_s'/\Lambda_s|^2< \mathcal{O}(1)$. This

Ygal Y. Klein, Boaz Katz

The very long-term evolution of the hierarchical restricted three-body problem with a slightly aligned precessing quadrupole potential is studied analytically. This problem describes the evolution of a star and a planet which are perturbed either by a (circular and not too inclined) binary star system or by one other star and a second more distant star, as w

Patrick Tscheppe, Jiawei Zang, Marcel Klett, Seher Karakuzu

The ability to control the properties of twisted bilayer transition metal dichalcogenides in situ makes them an ideal platform for investigating the interplay of strong correlations and geometric frustration. Of particular interest are the low energy scales, which make it possible to experimentally access both temperature and magnetic fields that are of the

M. Kliczkowski, R. Świętek, L. Vidmar, M. Rigol

To which degree the average entanglement entropy of midspectrum eigenstates of quantum-chaotic interacting Hamiltonians agrees with that of random pure states is a question that has attracted considerable attention in the recent years. While there is substantial evidence that the leading (volume-law) terms are identical, which and how subleading terms differ

Prantik Sarmah, Sovan Chakraborty, Irene Tamborra, Katie Auchettl

Observations of some supernovae (SNe), such as SN 2014C, in the X-ray and radio wavebands revealed a rebrightening over a timescale of about a year since their detection. Such a discovery hints towards the evolution of a hydrogen-poor SN of Type Ib/c into a hydrogen-rich SN of Type IIn, the late time activity being attributed to the interaction of the SN eje

Stefano Marchesi, Marco Mignoli, Roberto Gilli, Giovanni Mazzolari

We present the results of a spectroscopic campaign with the Multi-Object Double Spectrograph (MODS) instrument mounted on the Large Binocular Telescope (LBT), aimed at obtaining a spectroscopic redshift for seven Chandra J1030 sources with a photometric redshift >=2.7 and optical magnitude r_AB=[24.5-26.5]. We obtained a spectroscopic redshift for five out o

Viola Gelli, Stefania Salvadori, Andrea Ferrara, Andrea Pallottini

The surprising JWST discovery of a quiescent, low-mass ($M_\star=10^{8.7} \rm M_\odot$) galaxy at redshift $z=7.3$ (JADES-GS-z7-01-QU) represents a unique opportunity to study the imprint of feedback processes on early galaxy evolution. We build a sample of 130 low-mass ($M_\star\lesssim 10^{9.5} \rm M_\odot$) galaxies from the SERRA cosmological zoom-in sim

Kevin B. Burdge, Kareem El-Badry, Saul Rappaport, Tin Long Sunny Wong

We report the discovery of ZTF J0127+5258, a compact mass-transferring binary with an orbital period of 13.7 minutes. The system contains a white dwarf accretor, which likely originated as a post-common envelope carbon-oxygen (CO) white dwarf, and a warm donor ($T_{\rm eff,\,donor}= 16,400\pm1000\,\rm K$). The donor probably formed during a common envelope p

Sudip Jana, Yago Porto

We investigate the effect of resonant spin conversion of the neutrinos induced by the geometrical phase in a twisting magnetic field. We find that the geometrical phase originating from the rotation of the transverse magnetic field along the neutrino trajectory can trigger a new resonant spin conversion of Dirac neutrinos inside the supernova, even if there

Medhini Narasimhan, Licheng Yu, Sean Bell, Ning Zhang

Given the enormous number of instructional videos available online, learning a diverse array of multi-step task models from videos is an appealing goal. We introduce a new pre-trained video model, VideoTaskformer, focused on representing the semantics and structure of instructional videos. We pre-train VideoTaskformer using a simple and effective objective:

Relja Arandjelović, Alex Andonian, Arthur Mensch, Olivier J. Hénaff

The core problem in zero-shot open vocabulary detection is how to align visual and text features, so that the detector performs well on unseen classes. Previous approaches train the feature pyramid and detection head from scratch, which breaks the vision-text feature alignment established during pretraining, and struggles to prevent the language model from f

Ioannis Argyriou, Craig Lage, George H. Rieke, Danny Gasman

The Mid-Infrared Instrument (MIRI) on board the James Webb Space Telescope (JWST) uses three Si:As impurity band conduction (IBC) detector arrays. The output voltage level of each MIRI detector pixel is digitally recorded by sampling-up-the-ramp. For uniform or low-contrast illumination, the pixel ramps become non-linear in a predictable way, but in areas of

Nupur Kumari, Bingliang Zhang, Sheng-Yu Wang, Eli Shechtman

Large-scale text-to-image diffusion models can generate high-fidelity images with powerful compositional ability. However, these models are typically trained on an enormous amount of Internet data, often containing copyrighted material, licensed images, and personal photos. Furthermore, they have been found to replicate the style of various living artists or

Lucy Chai, Richard Tucker, Zhengqi Li, Phillip Isola

Despite increasingly realistic image quality, recent 3D image generative models often operate on 3D volumes of fixed extent with limited camera motions. We investigate the task of unconditionally synthesizing unbounded nature scenes, enabling arbitrarily large camera motion while maintaining a persistent 3D world model. Our scene representation consists of a

Mehmet Aygün, Oisin Mac Aodha

We introduce SAOR, a novel approach for estimating the 3D shape, texture, and viewpoint of an articulated object from a single image captured in the wild. Unlike prior approaches that rely on pre-defined category-specific 3D templates or tailored 3D skeletons, SAOR learns to articulate shapes from single-view image collections with a skeleton-free part-based

Pei-Xin Shen, Vivien Perrin, Mircea Trif, Pascal Simon

A chain of magnetic impurities deposited on the surface of a superconductor can form a topological Shiba band that supports Majorana zero modes and holds a promise for topological quantum computing. Yet, most experiments scrutinizing these zero modes rely on transport measurements, which only capture local properties. Here we propose to leverage the intrinsi

Stephanie Milani, Anssi Kanervisto, Karolis Ramanauskas, Sander Schulhoff

To facilitate research in the direction of fine-tuning foundation models from human feedback, we held the MineRL BASALT Competition on Fine-Tuning from Human Feedback at NeurIPS 2022. The BASALT challenge asks teams to compete to develop algorithms to solve tasks with hard-to-specify reward functions in Minecraft. Through this competition, we aimed to promot

Zhanghan Ke, Yuhao Liu, Lei Zhu, Nanxuan Zhao

In this paper, we present a Neural Preset technique to address the limitations of existing color style transfer methods, including visual artifacts, vast memory requirement, and slow style switching speed. Our method is based on two core designs. First, we propose Deterministic Neural Color Mapping (DNCM) to consistently operate on each pixel via an image-ad

Runsen Xu, Tai Wang, Wenwei Zhang, Runjian Chen

This paper introduces the Masked Voxel Jigsaw and Reconstruction (MV-JAR) method for LiDAR-based self-supervised pre-training and a carefully designed data-efficient 3D object detection benchmark on the Waymo dataset. Inspired by the scene-voxel-point hierarchy in downstream 3D object detectors, we design masking and reconstruction strategies accounting for

Zeqi Xiao, Wenwei Zhang, Tai Wang, Chen Change Loy

DEtection TRansformer (DETR) started a trend that uses a group of learnable queries for unified visual perception. This work begins by applying this appealing paradigm to LiDAR-based point cloud segmentation and obtains a simple yet effective baseline. Although the naive adaptation obtains fair results, the instance segmentation performance is noticeably inf

Amit Raj, Srinivas Kaza, Ben Poole, Michael Niemeyer

We present DreamBooth3D, an approach to personalize text-to-3D generative models from as few as 3-6 casually captured images of a subject. Our approach combines recent advances in personalizing text-to-image models (DreamBooth) with text-to-3D generation (DreamFusion). We find that naively combining these methods fails to yield satisfactory subject-specific

Jan Verlage, Friedemann Queisser, Nikodem Szpak, Jürgen König

As a prototypical example for a heterostructure combining a weakly and a strongly interacting quantum many-body system, we study the interface between a semiconductor and a Mott insulator. Via the hierarchy of correlations, we derive and match the propagating or evanescent (quasi) particle solutions on both sides and assume that the interactions among the el

Eric J. Michaud, Ziming Liu, Uzay Girit, Max Tegmark

We propose the Quantization Model of neural scaling laws, explaining both the observed power law dropoff of loss with model and data size, and also the sudden emergence of new capabilities with scale. We derive this model from what we call the Quantization Hypothesis, where network knowledge and skills are "quantized" into discrete chunks ($\textbf{quanta}$)

Andong Deng, Taojiannan Yang, Chen Chen

The goal of building a benchmark (suite of datasets) is to provide a unified protocol for fair evaluation and thus facilitate the evolution of a specific area. Nonetheless, we point out that existing protocols of action recognition could yield partial evaluations due to several limitations. To comprehensively probe the effectiveness of spatiotemporal represe

Jeya Maria Jose Valanarasu, Rahul Garg, Andeep Toor, Xin Tong

Most video restoration networks are slow, have high computational load, and can't be used for real-time video enhancement. In this work, we design an efficient and fast framework to perform real-time video enhancement for practical use-cases like live video calls and video streams. Our proposed method, called Recurrent Bottleneck Mixer Network (ReBotNet), em

Marco Drewes, Lei Ming, Isabel Oldengott

We study the sensitivity of LiteBIRD and CMB-S4 to the reheating temperature and the inflaton coupling in three types of plateau-potential models of inflation, namely mutated hilltop inflation, radion gauge inflation, and $\alpha$-attractor T models. We first find relations between model parameters and CMB observables in all models. We then perform Monte Car

Michele Del Zotto, Muyang Liu, Paul-Konstantin Oehlmann

We review here some aspects of our recent works about the geometric engineering of heterotic little string theories using F-theory. Building on the seminal work by Aspinwall and Morrison as well as Intrilligator and Blum, we solve some longstanding open questions thanks to recent progress in our understanding of 6D (1,0) theories and their generalized symmet

Nathan Mankovich, Tolga Birdal

This paper presents a new, provably-convergent algorithm for computing the flag-mean and flag-median of a set of points on a flag manifold under the chordal metric. The flag manifold is a mathematical space consisting of flags, which are sequences of nested subspaces of a vector space that increase in dimension. The flag manifold is a superset of a wide rang

Puja Trivedi, Danai Koutra, Jayaraman J. Thiagarajan

Advances in the expressivity of pretrained models have increased interest in the design of adaptation protocols which enable safe and effective transfer learning. Going beyond conventional linear probing (LP) and fine tuning (FT) strategies, protocols that can effectively control feature distortion, i.e., the failure to update features orthogonal to the in-d

Jiajie Guo, Jordi Tura, Qiongyi He, Matteo Fadel

We expand the toolbox for studying Bell correlations in multipartite systems by introducing permutationally invariant Bell inequalities (PIBIs) involving few-body correlators. First, we present around twenty families of PIBIs with up to three- or four-body correlators, that are valid for arbitrary number of particles. Compared to known inequalities, these sh

Xin Lu, Jia-Xin Zhang, Shou-Shu Gong, D. N. Sheng

Understanding the doped Mott insulator is a central challenge in condensed matter physics. In this work, we first explicitly identify a new sign structure in the $t$-$t'$-$J$ model on the square lattice that replaces the conventional Fermi statistics for weakly interacting electrons. Then we show that the singular, i.e., the phase-string part of the sign str

Yaojie Hu, Jin Tian

Can a Python program be executed statement-by-statement by neural networks composed according to the source code? We formulate the Neuro-Symbolic Execution Problem and introduce Neural Interpretation (NI), the first neural model for the execution of generic source code that allows missing definitions. NI preserves source code structure, where every variable

Ananta R. Bhattarai, Matthias Nießner, Artem Sevastopolsky

Recent progress in NeRF-based GANs has introduced a number of approaches for high-resolution and high-fidelity generative modeling of human heads with a possibility for novel view rendering. At the same time, one must solve an inverse problem to be able to re-render or modify an existing image or video. Despite the success of universal optimization-based met

Mannat Singh, Quentin Duval, Kalyan Vasudev Alwala, Haoqi Fan

This paper revisits the standard pretrain-then-finetune paradigm used in computer vision for visual recognition tasks. Typically, state-of-the-art foundation models are pretrained using large scale (weakly) supervised datasets with billions of images. We introduce an additional pre-pretraining stage that is simple and uses the self-supervised MAE technique t

Ziqi Huang, Tianxing Wu, Yuming Jiang, Kelvin C. K. Chan

Diffusion models gain increasing popularity for their generative capabilities. Recently, there have been surging needs to generate customized images by inverting diffusion models from exemplar images, and existing inversion methods mainly focus on capturing object appearances (i.e., the "look"). However, how to invert object relations, another important pill

Gaia Belardinelli, Thomas Bolander

Attention is the crucial cognitive ability that limits and selects what information we observe. Previous work by Bolander et al. (2016) proposes a model of attention based on dynamic epistemic logic (DEL) where agents are either fully attentive or not attentive at all. While introducing the realistic feature that inattentive agents believe nothing happens, t

Hanna Bogucka, Bartosz Kopras, Filip Idzikowski, Bartosz Bossy

Fog computing allows computationally-heavy problems with tight time constraints to be solved even if end devices have limited computational resources and latency induced by cloud computing is too high. How can energy consumed by fog computing be saved while obeying latency constraints and considering not only computations but also transmission through wirele

Jinmin Wang, Zhizhang Xie

In this paper, we prove a dihedral extremality and rigidity theorem for a large class of codimension zero submanifolds with polyhedral boundary in warped product manifolds. We remark that the spaces considered in this paper are not necessarily warped product manifolds themselves. In particular, the results of this paper are applicable to submanifolds (of war

Jiehui Zhou, Xumeng Wang, Jie Wang, Hui Ye

Collusive fraud, in which multiple fraudsters collude to defraud health insurance funds, threatens the operation of the healthcare system. However, existing statistical and machine learning-based methods have limited ability to detect fraud in the scenario of health insurance due to the high similarity of fraudulent behaviors to normal medical visits and the

Giuliano Basso, Denis Marti, Stefan Wenger

We study metric spaces homeomorphic to a closed oriented manifold from both geometric and analytic perspectives. We show that such spaces (which are sometimes called metric manifolds) admit a non-trivial integral current without boundary, provided they satisfy some weak assumptions. The existence of such an object should be thought of as an analytic analog o

Tongzhou Mu, Hao Su

Although reinforcement learning has seen tremendous success recently, this kind of trial-and-error learning can be impractical or inefficient in complex environments. The use of demonstrations, on the other hand, enables agents to benefit from expert knowledge rather than having to discover the best action to take through exploration. In this survey, we disc

Visakan Balakumar, Rafael Bernar, Elizabeth Winstanley

We consider the definition of the Boulware and Hartle-Hawking states for quantum fields on black hole space-times. The properties of these states on a Schwarzschild black hole have been understood for many years, but neither of these states has a direct analogue on a Kerr black hole. We show how superradiant modes play an important role in the definition of

Charles-Philippe Diez

In this paper, we provide new results about the free Malliavin calculus on the Wigner space first developed in the breakthrough work of Biane and Speicher. We define in this way the higher-order Malliavin derivatives, and we study their associated Sobolev-Wigner spaces. Using these definitions, we are able to obtain a free counterpart of the of the Stroock f

Vitaliy Kurlin

A basic representation of any real molecule is a finite cloud of unordered atoms, many of which are chemically indistinguishable. A natural equivalence on point clouds in any metric space is defined by isometries that are distance-preserving transformations. In a Euclidean space, any isometry is a composition of translations, rotations, and reflections. If p

Karim Banawan, Ahmed Arafa, Karim G. Seddik

We consider a multi-process remote estimation system observing $K$ independent Ornstein-Uhlenbeck processes. In this system, a shared sensor samples the $K$ processes in such a way that the long-term average sum mean square error (MSE) is minimized using signal-independent sampling policies, in which sampling instances are chosen independently from the proce

Sandeep Avula, Bogeum Choi, Jaime Arguello

In the last decade, conversational search has attracted considerable attention. However, most research has focused on systems that can support a \emph{single} searcher. In this paper, we explore how systems can support \emph{multiple} searchers collaborating over an instant messaging platform (i.e., Slack). We present a ``Wizard of Oz'' study in which 27 par

Joy Hsu, Jiayuan Mao, Jiajun Wu

Grounding object properties and relations in 3D scenes is a prerequisite for a wide range of artificial intelligence tasks, such as visually grounded dialogues and embodied manipulation. However, the variability of the 3D domain induces two fundamental challenges: 1) the expense of labeling and 2) the complexity of 3D grounded language. Hence, essential desi

Sameer Pai, Tao Chen, Megha Tippur, Edward Adelson

We study the problem of object retrieval in scenarios where visual sensing is absent, object shapes are unknown beforehand and objects can move freely, like grabbing objects out of a drawer. Successful solutions require localizing free objects, identifying specific object instances, and then grasping the identified objects, only using touch feedback. Unlike

Lizzie Buchanan

We provide a new bound on the maximum degree of the Jones polynomial of a positive link with second Jones coefficient equal to $\pm 1$ or $\pm 2$. This builds upon the result of our previous work, in which we found such a bound for positive fibered links. We also show that each of these three bounds obstruct positivity for infinitely many almost-positive dia

Tobias Barthel, Natalia Castellana, Drew Heard, Beren Sanders

We develop a theory of cosupport and costratification in tensor triangular geometry. We study the geometric relationship between support and cosupport, provide a conceptual foundation for cosupport as categorically dual to support, and discover surprising relations between the theory of costratification and the theory of stratification. We prove that many ca

Jianhui Liu, Yukang Chen, Xiaoqing Ye, Xiaojuan Qi

Category-level 6D pose estimation aims to predict the poses and sizes of unseen objects from a specific category. Thanks to prior deformation, which explicitly adapts a category-specific 3D prior (i.e., a 3D template) to a given object instance, prior-based methods attained great success and have become a major research stream. However, obtaining category-sp

Jacob Bringewatt, Michael Jarret, T. C. Mooney

We prove an adiabatic theorem that applies at timescales short of the typical adiabatic limit. Our proof analyzes the stability of solutions to Schrodinger's equation under perturbation. We directly characterize cross-subspace effects of perturbation, which are typically significantly less than suggested by the perturbation's operator norm. This stability ha